Complexity Classes: P and NPExplores complexity classes P and NP, highlighting solvable and verifiable problems, including NP-complete challenges.
P vs NP: Complexity TheoryDelves into complexity theory, focusing on the P vs NP problem and the classification of computational problems based on efficiency.
Approximation AlgorithmsCovers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Solving Parity Games in PracticeExplores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.
Dynamic Programming: KnapsackExplores dynamic programming for the Knapsack problem, discussing strategies, algorithms, NP-hardness, and time complexity analysis.
Elements of Computational ComplexityIntroduces computational complexity, decision problems, quantum complexity, and probabilistic algorithms, including NP-hard and NP-complete problems.
Optimization AlgorithmsCovers optimization algorithms, convergence properties, and time complexity of sequences and functions.
Optimisation in Energy SystemsExplores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.
